Comparative analysis of artificial intelligence methods for streamflow forecasting

Comparative analysis of artificial intelligence methods for streamflow forecasting

Deep learning excels at managing spatial and temporal time series with variable patterns for streamflow forecasting, but traditional machine learning algorithms may struggle with complicated data, including non-linear and multidimensional complexity. Empirical heterogeneity within watersheds and lim...

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Bibliographic Details
Main Authors: Wei, Yaxing, Bin Hashim, Huzaifa, Lai, Sai Hin, Chong, Kai Lun, Huang, Yuk Feng, Ahmed, Ali Najah, Sherif, Mohsen, El-Shafie, Ahmed
Format: Article
Published: Institute of Electrical and Electronics Engineers 2024
Subjects:
QA75 Electronic computers. Computer science
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.um.edu.my/44211/
https://doi.org/10.1109/ACCESS.2024.3351754
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Institution: Universiti Malaya

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http://eprints.um.edu.my/44211/
https://doi.org/10.1109/ACCESS.2024.3351754

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